Abstract
Massive multiple-input-multiple-output (MIMO) is a fifth-generation wireless technology that equips the cellular base stations (BSs) with a very large number of antenna and is a communication technique of serving several users. Aiming at the problem of the high computational complexity of linear channel estimation and linear decoding in massive MIMO systems, this study proposes two low-complexity decoding algorithms according to the characteristics of the system. The fast decoding algorithm is designed by using the asymptotic orthogonality of the channel in the system to avoid solving the inverse of the channel matrix. In combination with increasing the number of base BS antennas to optimise user channel characteristics, a simple operator decoding algorithm is designed to realise direct decoding without estimating the channel. Simulation results show that the proposed algorithms can effectively reduce the computational complexity while ensuring system performance.